Optimization of Iron Oxide Tracer Synthesis for Magnetic Particle Imaging
Why this work is in the frame
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Bibliographic record
Abstract
The optimization of iron oxide nanoparticles as tracers for magnetic particle imaging (MPI) alongside the development of data acquisition equipment and image reconstruction techniques is crucial for the required improvements in image resolution and sensitivity of MPI scanners. We present a large-scale water-based synthesis of multicore superparamagnetic iron oxide nanoparticles stabilized with dextran (MC-SPIONs). We also demonstrate the preparation of single core superparamagnetic iron oxide nanoparticles in organic media, subsequently coated with a poly(ethylene glycol) gallic acid polymer and phase transferred to water (SC-SPIONs). Our aim was to obtain long-term stable particles in aqueous media with high MPI performance. We found that the amplitude of the third harmonic measured by magnetic particle spectroscopy (MPS) at 10 mT is 2.3- and 5.8-fold higher than Resovist for the MC-SPIONs and SC-SPIONs, respectively, revealing excellent MPI potential as compared to other reported MPI tracer particle preparations. We show that the reconstructed MPI images of phantoms using optimized multicore and specifically single-core particles are superior to that of commercially available Resovist, which we utilize as a reference standard, as predicted by MPS.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it